[JTH] add scipy RBF interpolator to test with real data

bluemath_tk/core/logging.py

@@ -37,12 +37,12 @@ def get_file_logger(
     >>> # 2023-10-22 14:55:23,456 - my_app_logger - INFO - This is an info message.
     >>> # 2023-10-22 14:55:23,457 - my_app_logger - WARNING - This is a warning message.
     >>> # 2023-10-22 14:55:23,458 - my_app_logger - ERROR - This is an error message.
-
-    Notes
-    -----
-    - TODO: Check a way to remove existing loggers to avoid duplicate logs.
     """
 
+    # If a logger with the specified name already exists, return it
+    if name in logging.Logger.manager.loggerDict:
+        return logging.getLogger(name)
+
     # Create a logger with the specified name
     logger = logging.getLogger(name)
     logger.setLevel(level)

bluemath_tk/interpolation/_base_interpolation.py

@@ -1,4 +1,6 @@
 from abc import abstractmethod
+from typing import List
+import pandas as pd
 from ..core.models import BlueMathModel
 
 
@@ -62,3 +64,31 @@ def fit_predict(self, *args, **kwargs):
         """
 
         pass
+
+
+class InterpolationComparator:
+    """
+    Class for comparing interpolation models.
+    """
+
+    def __init__(self, list_of_models: List[BaseInterpolation]) -> None:
+        """
+        Initializes the InterpolationComparator class.
+        """
+
+        self.list_of_models = list_of_models
+
+    def fit(
+        self,
+        subset_data: pd.DataFrame,
+        target_data: pd.DataFrame,
+    ) -> None:
+        """
+        Fits the clustering models.
+        """
+
+        for model in self.list_of_models:
+            model.fit(
+                subset_data=subset_data,
+                target_data=target_data,
+            )